187 research outputs found

    Classical Opacity

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    Philosophy and Phenomenological Research, EarlyView

    On the Recursive Enumerability of Fixed-Point Combinators

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    We show that the set of fixed-point combinators forms a recursively-enumerable subset of a larger set of terms we call non-standard fixed-point combinators. These terms are observationally equivalent to fixed-point combinators in any computable context, but the set of on-standard fixed-point combinators is not recursively enumerable

    On the Recursive Enumerability of Fixed-Point Combinators

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    We show that the set of fixed-point combinators forms a recursively-enumerable subset of a larger set of terms that is (A) not recursively enumerable, and (B) the terms of which are observationally equivalent to fixed-point combinators in any computable context

    Algebraic specialization of generic functions for recursive types

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    Defining functions over large, possibly recursive, data structures usually involves a lot of boilerplate. This code simply traverses non-interesting parts of the data, and rapidly becomes a maintainability problem. Many generic programming libraries have been proposed to address this issue. Most of them allow the user to specify the behavior just for the interesting bits of the structure, and provide traversal combinators to “scrap the boilerplate”. The expressive power of these libraries usually comes at the cost of efficiency, since runtime checks are used to detect where to apply the type-specific behavior. In previous work we have developed an effective rewrite system for specialization and optimization of generic programs. In this paper we extend it to also cover recursive data types. The key idea is to specialize traversal combinators using well-known recursion patterns, such as folds or paramorphisms. These are ruled by a rich set of algebraic laws that enable aggressive optimizations. We present a type-safe encoding of this rewrite system in Haskell, based on recent language extensions such as type-indexed type families

    The Environment as an Argument

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    Context-awareness as defined in the setting of Ubiquitous Computing [3] is all about expressing the dependency of a specific computation upon some implicit piece of information. The manipulation and expression of such dependencies may thus be neatly encapsulated in a language where computations are first-class values. Perhaps surprisingly however, context-aware programming has not been explored in a functional setting, where first-class computations and higher-order functions are commonplace. In this paper we present an embedded domain-specific language (EDSL) for constructing context-aware applications in the functional programming language Haskell. © 2012 Springer-Verlag

    Learning Computer Programs with the Bayesian Optimization Algorithm

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    The hierarchical Bayesian Optimization Algorithm (hBOA) [24, 25] learns bit-strings by constructing explicit centralized models of a population and using them to generate new instances. This thesis is concerned with extending hBOA to learning open-ended program trees. The new system, BOA programming (BOAP), improves on previous probabilistic model building GP systems (PMBGPs) in terms of the expressiveness and open-ended flexibility of the models learned, and hence control over the distribution of individuals generated. BOAP is studied empirically on a toy problem (learning linear functions) in various configurations, and further experimental results are presented for two real-world problems: prediction of sunspot time series, and human gene function inference
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